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In the preliminary SNN, the neuronal information is simply encoded by the firing rate, which limits the volume of information in a certain spike pattern. Studies of the biological nervous system have discovered neuronal cooperativity, where flow of neural information is collaboratively encoded and carried by the spatiotemporal stamp and the correlated neuronal activity. In this study, by encoding the control pattern on the dual gates, a MoS<jats:sub>2<\/jats:sub>\u2010based neuristor is exploited to program spatiotemporal information and neuronal correlations via the device's internal dynamics as well as the network topology, and a spiking correlated neural network (SCNN) is demonstrated. This correlated neural network not only succeeds in identifying the patterns with translational and rotational symmetry but also correctly reveals the rotated angles. Compared with conventional SNNs, the dimension of information flow in SCNNs can be greatly enlarged by taking advantage of the synergy between the rate coding and the neuronal correlations. This proof\u2010of\u2010concept work provides the potential to achieve high\u2010volume information processing with the simplified circuitry of neuromorphic computing systems.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202000102","type":"journal-article","created":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T01:57:02Z","timestamp":1598579822000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Rotational Pattern Recognition by Spiking Correlated Neural Network Based on Dual\u2010Gated MoS<sub>2<\/sub> Neuristor"],"prefix":"10.1002","volume":"2","author":[{"given":"Lin","family":"Bao","sequence":"first","affiliation":[{"name":"Institute of Microelectronics Peking University  Beijing 100871 P. R. 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